Instructions to use SaulLu/recreate-history with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaulLu/recreate-history with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SaulLu/recreate-history")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SaulLu/recreate-history") model = AutoModelForTokenClassification.from_pretrained("SaulLu/recreate-history", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SaulLu/recreate-history: direct link, hf CLI and curl.
- Browser
- Download file 67.6 MB
-
https://huggingface.co/SaulLu/recreate-history/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SaulLu/recreate-history/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SaulLu/recreate-history/resolve/main/pytorch_model.bin
67.6 MB
- Xet hash:
- d9c7a72313c5cee974296046aff7a5f38dec8f3aacd2896b568455f4927f4029
- Size of remote file:
- 67.6 MB
- SHA256:
- b9eed85cefc5e1e409fcb968fce7ad1741e9cb85e006dade982af6bf58b74ec2
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